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⚛️ In React, rendering large lists or tables can be a drag on performance. The fix? Virtualization! the process of only rendering part of that large data set (just enough to fill the viewport). ✅ Improves rendering time significantly. ✅ Lowers memory consumption.

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George Moller

119,062 subscribers

55,288 görüntüleme • 1 yıl önce •via X (Twitter)

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⚛️ I don't worry too much about re-renders in React. (unless I see performance issues) However, I do care about understanding how the rendering process works. ↓
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⚛️ I don't worry too much about re-renders in React. (unless I see performance issues) However, I do care about understanding how the rendering process works. ↓

George Moller

38,567 görüntüleme • 2 yıl önce

Real-time rendering using #unity3d , part of the girl's face
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Real-time rendering using #unity3d , part of the girl's face

Sakura Rabbit 樱花兔

164,641 görüntüleme • 3 yıl önce

Before rendering// after rendering The animation edition this time😅🙃💀
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Before rendering// after rendering The animation edition this time😅🙃💀

D.SLOOGS ⚡️EVO VEGAS + ANIME EXPO💀

321,397 görüntüleme • 2 yıl önce

EEVEE rendering can be so damn fast when the settings are set right #b3d
0:15

EEVEE rendering can be so damn fast when the settings are set right #b3d

Gleb Alexandrov

31,960 görüntüleme • 6 ay önce

woww.. AI can literally do 3D rendering now just upload a draft 3D animation, it turns it into cinematic film scene you can control the looks of the car and environment with image refs no need days of rendering anymore..
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woww.. AI can literally do 3D rendering now just upload a draft 3D animation, it turns it into cinematic film scene you can control the looks of the car and environment with image refs no need days of rendering anymore..

el.cine

112,797 görüntüleme • 5 ay önce

Here's the whole process step by step. I began to focus far more on construction than I had previously. It appears to save a significant amount of time when rendering.
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Here's the whole process step by step. I began to focus far more on construction than I had previously. It appears to save a significant amount of time when rendering.

Dariusz Kieliszek

15,522 görüntüleme • 1 yıl önce

Bounded rendering in #ConjureSDF v0.3, a free update to support Blender 4.5+ Full release later this month. Speeds up rendering by only caring about pixels covered by the bounds of SDF groups. #blender3d #b3d #blender #3dart #3dmodeling
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Bounded rendering in #ConjureSDF v0.3, a free update to support Blender 4.5+ Full release later this month. Speeds up rendering by only caring about pixels covered by the bounds of SDF groups. #blender3d #b3d #blender #3dart #3dmodeling

João Desager

13,704 görüntüleme • 8 ay önce

Introducing Kaleido💮 from AI at Meta — a universal generative neural rendering engine for photorealistic, unified object and scene view synthesis. Kaleido is built on a simple but powerful design philosophy: 3D perception is a form of visual common sense. Following this idea, we formulate rendering purely as a sequence-to-sequence generation problem, successfully unifying neural rendering with the architecture principles behind modern language and video models. Unlike traditional neural rendering methods, Kaleido learns 3D purely in a data-driven way, without explicit 3D representations or structures. It acquires spatial understanding directly through large-scale video pretraining, then multi-view 3D data finetuning, inspired by how LLMs acquire textual common sense from large corpora before specialising in domains like coding. Through extensive ablations, we progressively modernised the architecture design and training strategies and tackled key scaling challenges in sequence-to-sequence generative rendering, arriving at a design that’s simple, versatile, and scalable. Kaleido significantly outperforms prior generative models in few-view settings, and remarkably is the first zero-shot generative method matches InstantNGP-level rendering quality in multi-view settings. We view Kaleido also as an alternative step towards world modeling that flexibly spans a spectrum of “realities": with many views, it faithfully reconstructs grounded reality; with fewer views, it imagines plausible unseen details. 🔗 Explore more results and paper:
0:12

Introducing Kaleido💮 from AI at Meta — a universal generative neural rendering engine for photorealistic, unified object and scene view synthesis. Kaleido is built on a simple but powerful design philosophy: 3D perception is a form of visual common sense. Following this idea, we formulate rendering purely as a sequence-to-sequence generation problem, successfully unifying neural rendering with the architecture principles behind modern language and video models. Unlike traditional neural rendering methods, Kaleido learns 3D purely in a data-driven way, without explicit 3D representations or structures. It acquires spatial understanding directly through large-scale video pretraining, then multi-view 3D data finetuning, inspired by how LLMs acquire textual common sense from large corpora before specialising in domains like coding. Through extensive ablations, we progressively modernised the architecture design and training strategies and tackled key scaling challenges in sequence-to-sequence generative rendering, arriving at a design that’s simple, versatile, and scalable. Kaleido significantly outperforms prior generative models in few-view settings, and remarkably is the first zero-shot generative method matches InstantNGP-level rendering quality in multi-view settings. We view Kaleido also as an alternative step towards world modeling that flexibly spans a spectrum of “realities": with many views, it faithfully reconstructs grounded reality; with fewer views, it imagines plausible unseen details. 🔗 Explore more results and paper:

Shikun Liu

21,843 görüntüleme • 8 ay önce

Using the id modifier on subviews throws a wrench into List's optimization. Instead of just rendering what's visible, it forces all subviews to load instantly. To avoid this, build data sources that align with the Identifiable protocol.
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Using the id modifier on subviews throws a wrench into List's optimization. Instead of just rendering what's visible, it forces all subviews to load instantly. To avoid this, build data sources that align with the Identifiable protocol.

fatbobman (东坡肘子)

45,936 görüntüleme • 1 yıl önce

Another large speedup to SDF brick rendering (-20-40%) that is obvious in hindsight: When baking bricks, calculate the texel bounds that actually contain the surface, and then rasterize/ray-march just those bounds rather than the full brick bounds. 1/
0:17

Another large speedup to SDF brick rendering (-20-40%) that is obvious in hindsight: When baking bricks, calculate the texel bounds that actually contain the surface, and then rasterize/ray-march just those bounds rather than the full brick bounds. 1/

Mike Turitzin

11,310 görüntüleme • 1 yıl önce

Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering discuss: The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formation process. While recent large-scale diffusion models have shown strong generative and inpainting capabilities, we find that current models do not sufficiently "understand" the scene shown in a single picture to generate consistent lighting effects (shadows, bright reflections, etc.) while preserving the identity and details of the composited object. We propose using a personalized large diffusion model as guidance to a physically based inverse rendering process. Our method recovers scene lighting and tone-mapping parameters, allowing the photorealistic composition of arbitrary virtual objects in single frames or videos of indoor or outdoor scenes. Our physically based pipeline further enables automatic materials and tone-mapping refinement.
0:15

Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering discuss: The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formation process. While recent large-scale diffusion models have shown strong generative and inpainting capabilities, we find that current models do not sufficiently "understand" the scene shown in a single picture to generate consistent lighting effects (shadows, bright reflections, etc.) while preserving the identity and details of the composited object. We propose using a personalized large diffusion model as guidance to a physically based inverse rendering process. Our method recovers scene lighting and tone-mapping parameters, allowing the photorealistic composition of arbitrary virtual objects in single frames or videos of indoor or outdoor scenes. Our physically based pipeline further enables automatic materials and tone-mapping refinement.

AK

19,101 görüntüleme • 1 yıl önce

Sparse allocation/rendering of SDF bricks is now working! The pipeline is fully GPU-driven - a series of compute shaders that manages brick allocation/baking in a 3D texture atlas, followed by draw-indirect for rendering. Still a lot more work to do, including automatic LOD.
0:17

Sparse allocation/rendering of SDF bricks is now working! The pipeline is fully GPU-driven - a series of compute shaders that manages brick allocation/baking in a 3D texture atlas, followed by draw-indirect for rendering. Still a lot more work to do, including automatic LOD.

Mike Turitzin

39,001 görüntüleme • 1 yıl önce

Partial rendering in Next.js 13. "Only the route segments that change on navigation re-render on the client, and any shared segments are preserved"
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Partial rendering in Next.js 13. "Only the route segments that change on navigation re-render on the client, and any shared segments are preserved"

Alex Sidorenko

159,359 görüntüleme • 2 yıl önce

Alright. I got the simulator rendering smoothly outside of the simulator app.
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Alright. I got the simulator rendering smoothly outside of the simulator app.

Pedro Piñera

43,746 görüntüleme • 5 ay önce

🌍 Behind the Anvil engine Episode 2 Discover how Anvil’s large-scale rendering and scalability technologies make it possible to build a seamless open world, delivering high visual quality and performance across platforms. ▶️ Watch the full episode here:
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🌍 Behind the Anvil engine Episode 2 Discover how Anvil’s large-scale rendering and scalability technologies make it possible to build a seamless open world, delivering high visual quality and performance across platforms. ▶️ Watch the full episode here:

Assassin's Creed

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React Server Components bring rendering flexibility to the component level in Next.js. Hear from Aurora Scharff at Next.js Conf to learn about: • Async components • Efficient data management • Optimizing load times and interactivity Join us in SF or stream online on Oct 24.
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React Server Components bring rendering flexibility to the component level in Next.js. Hear from Aurora Scharff at Next.js Conf to learn about: • Async components • Efficient data management • Optimizing load times and interactivity Join us in SF or stream online on Oct 24.

Next.js

16,052 görüntüleme • 1 yıl önce

Is Google taking initial steps to enhance Street View? For some reason, Street View seems stuck in technology that feels outdated. I wonder if we'll see such improvements on the product side. Also, note how much better it performs in all aspects compared to Zip-NeRF in their presented material. It offers more details and fewer artifacts. Great work! "LODGE: Level-of-Detail Large-Scale Gaussian Splatting with Efficient Rendering" Contributions: • We propose a novel LOD representation for 3DGS which, unlike previous methods [27, 28, 17], does not recompute the list of used Gaussians at each frame. This allows for acceleration and compaction, enabling the rendering of large-scale scenes even on mobile devices. • We design a strategy to automatically select optimal hyperparameters for splitting LODs, whereas most other methods require manual tuning of hyperparameters for each 3D scene. • To further accelerate rendering, we split the scene into chunks and pre-compute sets of active Gaussians per chunk. • Finally, we introduce a novel opacity interpolation scheme to produce visually pleasing rendering and eliminate artifacts when transitioning between chunks.
0:19

Is Google taking initial steps to enhance Street View? For some reason, Street View seems stuck in technology that feels outdated. I wonder if we'll see such improvements on the product side. Also, note how much better it performs in all aspects compared to Zip-NeRF in their presented material. It offers more details and fewer artifacts. Great work! "LODGE: Level-of-Detail Large-Scale Gaussian Splatting with Efficient Rendering" Contributions: • We propose a novel LOD representation for 3DGS which, unlike previous methods [27, 28, 17], does not recompute the list of used Gaussians at each frame. This allows for acceleration and compaction, enabling the rendering of large-scale scenes even on mobile devices. • We design a strategy to automatically select optimal hyperparameters for splitting LODs, whereas most other methods require manual tuning of hyperparameters for each 3D scene. • To further accelerate rendering, we split the scene into chunks and pre-compute sets of active Gaussians per chunk. • Finally, we introduce a novel opacity interpolation scheme to produce visually pleasing rendering and eliminate artifacts when transitioning between chunks.

MrNeRF

62,511 görüntüleme • 1 yıl önce

Just a heads up that you should never be rendering 10,000 lines of anything, especially if all the lines are the same height, as in code. List virtualisation is a very old and simple technique. You can experiment with the below at
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Just a heads up that you should never be rendering 10,000 lines of anything, especially if all the lines are the same height, as in code. List virtualisation is a very old and simple technique. You can experiment with the below at

Nic Barker

267,379 görüntüleme • 1 ay önce

Even in the midst of an accident, they just can’t help themselves, instead of rendering aid or calling 911, they whip out their phones and hit record.
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Even in the midst of an accident, they just can’t help themselves, instead of rendering aid or calling 911, they whip out their phones and hit record.

Liberacrat™️

440,944 görüntüleme • 1 yıl önce